AI Meets Business Rules and Process Management
Papers from the AAAI Spring Symposium
Knut Hinkelmann, Chair
Business rules and business process management are growing research and application areas for semantic technologies. While both areas make use of model driven knowledge representations—often in conjunction with application-oriented modeling tools—the potential of knowledge representations with precise semantics has only recently been recognized.
Generally, the areas of “business rules,” “semantic technologies,” and “business process management” are addressed by different communities at present. Standards are promoted by different organizations like W3C, OMG, and WfMC. Current research and practice, however, begins to identify and explore the benefits for combining methodologies from these different areas.
Business rules, for example, strive to meet the increasing requirements of transparency and compliance, making sure that all stakeholders comply with all rules and regulations at any place and any time. Defining a commonly agreed vocabulary is a prerequisite for rule definitions. Recent standardization efforts try to bring semantics into business rules can benefit from AI’s knowledge representation research that strongly influenced also ontology engineering and the semantic web. Similar observations can be made for other aspects of rule based systems that have already been addressed earlier within AI (for example, rule capture, inferencing, and explanation).
In business process management there is increasing research interest in combining business process modelling and execution with semantic technologies. In particular, the concept of semantic web services promises a new level of agility in process execution where AI can contribute insights and technologies from knowledge representation, reasoning and planning. There have also been approaches to combine business processes and business rules to achieve flexibility and agility in process execution.